This model was conceived in 2010, now more than 10 years ago, and not very long after Git itself came into being. In those 10 years, git-flow (the branching model laid out in this article) has become hugely popular in many a software team to the point where people have started treating it like a standard of sorts — but unfortunately also as a dogma or panacea.

During those 10 years, Git itself has taken the world by a storm, and the most popular type of software that is being developed with Git is shifting more towards web apps — at least in my filter bubble. Web apps are typically continuously delivered, not rolled back, and you don't have to support multiple versions of the software running in the wild.

This is not the class of software that I had in mind when I wrote the blog post 10 years ago. If your team is doing continuous delivery of software, I would suggest to adopt a much simpler workflow (like GitHub flow) instead of trying to shoehorn git-flow into your team.

If, however, you are building software that is explicitly versioned, or if you need to support multiple versions of your software in the wild, then git-flow may still be as good of a fit to your team as it has been to people in the last 10 years. In that case, please read on.

To conclude, always remember that panaceas don't exist. Consider your own context. Don't be hating. Decide for yourself.

We launched our Backblaze S3 Compatible APIs in May of 2020 and released them for GA in July. After a launch, it’s easy to forget about the hard work that made it a reality. With that in mind, we’ve asked Malay Shah, our Senior Software Engineering Manager, to explain one of the challenges he found intriguing in the process. If you’re interested in developing your own APIs, or just curious about how ours have come to be, we think you’ll find Malay’s perspective interesting.

• The CAN bus, part 1 - Intro - 13 Dec 2018
  • The CAN bus, part 2 - Access - 14 Dec 2018
  • The CAN bus, part 3 - STM32 - 15 Dec 2018
  • The CAN bus, part 4 - JeeH API - 16 Dec 2018
  • The CAN bus, part 5 - Demo - 17 Dec 2018
  • The CAN bus, part 6 - Single-wire - 18 Dec 2018

There's not a single month where I don't have to explain this. I thought it'd be a good opportunity to write about this .gitignore file so everyone is up to date on this magic file.

I like to use Makefiles. I like to use Makefiles in Java. I like to use Makefiles in Erlang. I like to use Makefiles in Elixir. And most recently, I like to use Makefiles in Ruby. I think you, too, would like to use Makefiles in your environment, and the engineering community would benefit if more of us used Makefiles, in general.

Sometimes I am startled to realize, in the middle of a discussion,
that I have offended or hurt some of the people I’m talking with.

First, know and accept this: I have a friend who is a wizard. He is
an ancient and wise wizard, and we have tea together. One teatime,
I mentioned my talking troubles to my friend, and he said this:

“Yes, Sam, I’ll bet it is hard for you – holding controversial
religious beliefs, I mean.”

In the past few years, a technique called browser fingerprinting has received a lot of attention because of the risks it can pose to privacy. What is it? How is it used? What is Tor Browser doing against it? In this blog post, I’m here to answer these questions. Let’s get started!

Infrastructure as Code (IaC) is changing the way that we’re doing things. Some people think that it’s the motorway that we have to follow and be aligned with business, as a resume they want us to be agile.

The arrival of tools such as Ansible, Puppet, SaltStack, and Chef, have enabled sysadmins to maintain modular, automatable infrastructure. This time I would like to introduce the Terraform tool.

Terraform is a provisioning declarative tool that is based on the Infrastructure as Code paradigm. Terraform is a multipurpose composition tool: it composes multiple tiers (SaaS/PaaS/IaaS).

Terraform is not a cloud agnostic tool, but in combination with OpenNebula, it can be amazing. By taking advantage of the template concept it will allow us to deploy vm’s agnostically in different cloud providers, such as AWS, Azure or on premise cloud infrastructure.

When working with Ansible and Terraform, I felt there was a gap in the workflow, so I built a Terraform Provider for Ansible. It integrates with a Terraform Inventory script to connect machines in your Terraform state to Ansible. This article explains my thought process in designing this integration.

Warning: This post is long. While working through this massive server upgrade/migration process, tears were shed, many cuss words were said, along with a general feeling of frustration, which ultimately culminated into extreme happiness once the migration was completed. The scale and complexity of the implementation factor into the length of this post, and I’ll share my thought process on how this was executed, so here goes.

This article describes how to configure Windows to automate the logon process by storing your password and other pertinent information in the registry database. By using this feature, other users can start your computer and use the account that you establish to automatically log on.

Important The autologon feature is provided as a convenience. However, this feature may be a security risk. If you set a computer for autologon, anyone who can physically obtain access to the computer can gain access to all the computer's contents, including any networks it is connected to. Additionally, when autologon is turned on, the password is stored in the registry in plain text. The specific registry key that stores this value can be remotely read by the Authenticated Users group. This setting is recommended only for cases in which the computer is physically secured and steps have been taken to make sure that untrusted users cannot remotely access the registry.

In Python, a decorator is a design pattern that we can use to add new functionality to an already existing object without the need to modify its structure. A decorator should be called directly before the function that is to be extended. With decorators, you can modify the functionality of a method, a function, or a class dynamically without directly using subclasses. This is a good idea when you want to extend the functionality of a function that you don't want to directly modify. Decorator patterns can be implemented everywhere, but Python provides more expressive syntax and features for that.

This tutorial provides a basic Python programmer's introduction to working with protocol buffers. By walking through creating a simple example application, it shows you how to

Define message formats in a .proto file.
Use the protocol buffer compiler.
Use the Python protocol buffer API to write and read messages. 

This isn't a comprehensive guide to using protocol buffers in Python. For more detailed reference information, see the Protocol Buffer Language Guide, the Python API Reference, the Python Generated Code Guide, and the Encoding Reference.

Office 365 Advanced Threat Protection (Office 365 ATP) blocked many notable zero-day exploits in 2017. In our analysis, one activity group stood out: NEODYMIUM. This threat actor is remarkable for two reasons:

Its access to sophisticated zero-day exploits for Microsoft and Adobe software
Its use of an advanced piece of government-grade surveillance spyware FinFisher, also known as FinSpy and detected by Microsoft security products as Wingbird

FinFisher is such a complex piece of malware that, like other researchers, we had to devise special methods to crack it. We needed to do this to understand the techniques FinFisher uses to compromise and persist on a machine, and to validate the effectiveness of Office 365 ATP detonation sandbox, Windows Defender Advanced Threat Protection (Windows Defender ATP) generic detections, and other Microsoft security solutions.